An excerpt from Julia for Data Analysis by Bogumil Kaminski
Many languages designed for doing data science provide ways to perform vectorized operations, which is also often called broadcasting. In Julia, broadcasting is also supported. In this article you will see how to use it.
Read it if you’re a data scientist or anyone who works with lots of data, and if you’re interested in the Julia language.
From Pandas Workout by Reuven Lerner
This article discusses using multi indexes in Pandas.
From Pandas Workout by Reuven Lerner
This article discusses using Data Frames in Pandas.
An excerpt from Julia for Data Analysis by Bogumil Kaminski
This article shows you how to use Multiple Dispatch in Julia.
Read it if you’re a data scientist or anyone who works with lots of data, and if you’re interested in the Julia language.
From Engineering Deep Learning Systems by Chi Wang and Donald Szeto
This article presents what prospective readers can expect to learn from this book and why you should learn it.
Read it if you’re a software developer interested in transitioning your skills to the field of deep learning system design or an engineering-minded data scientist who want to build more effective delivery pipelines.
From Pandas Workout by Reuven Lerner
This article discusses cleaning data to use with Pandas.
From Full Stack Python Security by Dennis Byrne
HTTP sessions are a necessity for all but the most trivial web applications. Web applications use HTTP sessions to isolate the traffic, context, and state of each user. This is the basis for every form of online transaction. If you’re buying something on Amazon, messaging someone on Facebook, or transferring money from your bank, the server must be able to identify you across multiple requests. This illustrates these concepts with Django.
From The Well-Grounded Python Developer by Doug Farrell
This article, excerpted from chapter 10, covers
§ Persisting Data
§ Database Systems
§ Database Structures
§ Modeling Data with SQLAlchemy
From Automated Machine Learning in Action by Qingquan Song, Haifeng Jin, and Xia Hu
This article covers
• Defining and introducing the fundamental concepts of machine learning
• Describing the motivation for and high-level concepts of automated machine learning
From Publishing Python Packages by Dane Hillard This article covers the pieces of the Python build system itself, so you can learn how packages are built from scratch. Take 35% off Publishing Python Packages by entering fcchillard2 into the discount… Continue Reading →